I would like to compare two absorption spectra (or interferograms) and conclude whether between these two there are statistically significant differences at particular wavelength intervals. At the moment, I have data of two experiments that look like this:
# A tibble: 6 x 5 t x1 y1 x2 y2 <dbl> <dbl> <dbl> <dbl> <dbl> 1 3999. 0.0124 0.0132 0.0122 0.0113 2 3998. 0.0125 0.0130 0.0122 0.0116 3 3997. 0.0122 0.0131 0.0122 0.0113 4 3996. 0.0121 0.0136 0.0122 0.0114 5 3995. 0.0124 0.0139 0.0122 0.0122 6 3994. 0.0125 0.0141 0.0122 0.0129
The first column represents the wavenumber, the
x columns represent the absorbance of sample and the
y columns represent the absorbance of irradiated sample (before and after).
I was wondering whether I could compare these data (
y) as time series and if so, what could be the method to quantify the differences, if any, between the samples before and after irradiation. Maybe it's already been done and there is somewhere some information as to how to compare the spectra if the wavenumber is interpreted as time ($x$ axis).
I did the t-test in R and in both experiments the null hypothesis could not be rejected, although for the second experiment (
y2) the $p$ value was much lower than for the first. If I average the
y, and then plot both data, I see that there are visible differences at certain wavelength intervals. But how can I check for sure the differences between spectrums?
Here is a project with similar experiments by Zezell et al. . For statistical analysis they use ANOVA and Tukey's test, but how do I do it for the vectored data?
- Zezell, D. M.; Benetti, C.; Veloso, M. N.; Castro, P. A. A.; Ana, P. A. FTIR Spectroscopy Revealing the Effects of Laser and Ionizing Radiation on Biological Hard Tissues. J. Braz. Chem. Soc 2015. DOI: 10.5935/0103-5053.20150246.